U glavnom projektu odvodnjavanja Čuruško-Žabaljskog sliva iz 1966. godine, u svrhu određivanja koeficijenta oticaja i hidromodula odvodnjavanja, korišćene su formule autora Nemeta i Turazza. Ova metoda se ne pojavljuje u savremenoj literaturi, ali je činjenica da je ona svojevremeno korišćena prilikom analize slivova i projekto-vanja sistema za odvodnjavanje na području Vojvodine i Mađarske. U nastavku je predstavljen niz relacija koje su korišćene prilikom analize Čuruško-Žabaljskog sliva (Pantelić, 1966).
Polazna jednačina za proračun srednjeg hidromodula odvodnjavanja glasi:
catchment area (Pantelić, 1966).
The starting equation for the medial hydro-module of the drainage system:
Where: qs – is the medial hydro-module of drainage (l s-1 ha-1), α – run-off coefficient, h – relevant precipitation level (mm), t – relevant precipitation time length (days), τ – reach time, the path of a drop of water from the remotest part of the catchment to the reservoir (days).
If we multiply the equation above by the coefficient that indicates the ratio of maximum and medium run-off, which is 1.7 in the conditions that apply to Hungary (it can be used for Vojvodina too), we get the per unit hydro-module for maximum drainage - qmax (l s-1 ha-1):
The run-off coefficient plays an important role in determining the hydro-module for the run-off.
Several factors need to be known for determining this, such as: permeability, gradient, land cultivation method, type of soil surface. In the main plan for the Čurug-Žabalj drainage system (Pantelić, 1966), we can read that the functional changes in the run-off coefficient on a monthly basis are caused by the following:
(1) land gradient (α1);
(2) soil’s permeability (α2);
(3) land cover (α3).
For determining the partial coefficients of run-off, the values are provided in Table 7.1, 7.2 and 7.3, where the relevant values of the water flow specified in relation to the gradient, the permeability and the vegetation that covers the land can be found. The run-off coefficient equals the sum of the three coefficients given.
They used the pedologic map of Vojvodina for determining the α2 partial coefficient (Živković et al., 1972). Defining the α2 partial coefficient was done based on the proportions of various soil types and their permeability levels in the given area. In his study Miljković (2005) classifies soil into drainage categories, based on its chemical characteristics. He created the following five drainage classes and described them as follows:
(1) 1st drainage class – soil with naturally weak drainage characteristics, so its surface is very much threatened by excess water;
(2) 2nd drainage class – soil with naturally weak drainage characteristics, so its surface is under medium level threat from excess water;
(3) 3rd drainage class – soil with naturally insufficient drainage characteristics, so its surface is moderately threatened by excess water;
τ merodavna visina padavina (mm), t – trajanje merodavne kiše (dani), τ - vreme doti-caja kišne kapi sa najudaljenije tačke sliva do recipijenta (dani).
Množenjem prethodne jednačine sa koeficijentom koji predstavlja odnos mak-simalnog i srednjeg proticaja, i koji za Mađarske uslove iznosi 1,7 (primenjivo i za teritoriju Vojvodine), dobija se maksimalni jedinični hidromodul odvodnjavanja qmax (l s-1 ha-1):
catchment area (Pantelić, 1966).
The starting equation for the medial hydro-module of the drainage system:
Where: qs – is the medial hydro-module of drainage (l s-1 ha-1), α – run-off coefficient, h – relevant precipitation level (mm), t – relevant precipitation time length (days), τ – reach time, the path of a drop of water from the remotest part of the catchment to the reservoir (days).
If we multiply the equation above by the coefficient that indicates the ratio of maximum and medium run-off, which is 1.7 in the conditions that apply to Hungary (it can be used for Vojvodina too), we get the per unit hydro-module for maximum drainage - qmax (l s-1 ha-1):
The run-off coefficient plays an important role in determining the hydro-module for the run-off.
Several factors need to be known for determining this, such as: permeability, gradient, land cultivation method, type of soil surface. In the main plan for the Čurug-Žabalj drainage system (Pantelić, 1966), we can read that the functional changes in the run-off coefficient on a monthly basis are caused by the following:
(1) land gradient (α1);
(2) soil’s permeability (α2);
(3) land cover (α3).
For determining the partial coefficients of run-off, the values are provided in Table 7.1, 7.2 and 7.3, where the relevant values of the water flow specified in relation to the gradient, the permeability and the vegetation that covers the land can be found. The run-off coefficient equals the sum of the three coefficients given.
They used the pedologic map of Vojvodina for determining the α2 partial coefficient (Živković et al., 1972). Defining the α2 partial coefficient was done based on the proportions of various soil types and their permeability levels in the given area. In his study Miljković (2005) classifies soil into drainage categories, based on its chemical characteristics. He created the following five drainage classes and described them as follows:
(1) 1st drainage class – soil with naturally weak drainage characteristics, so its surface is very much threatened by excess water;
(2) 2nd drainage class – soil with naturally weak drainage characteristics, so its surface is under medium level threat from excess water;
(3) 3rd drainage class – soil with naturally insufficient drainage characteristics, so its surface is moderately threatened by excess water;
τ
Koeficijent oticaja igra važnu ulogu u određivanju hidromodula odvodnjavanja. Nje-govo određivanje zahteva poznavanje faktora, kao što su: propustljivost, nagib i način obrade zemljišta, kao i vrstu zemljišnog pokrivača. U glavnom projektu sistema za odvodnjavanje Čurug-Žabalj (Pantelić, 1966) se navodi da je funkcionalna promena koeficijenta oticaja po mesecima u funkciji:
(1) pada terena (α1);
(2) propustljivosti zemljišta (α2);
(3) obraslosti zemljišta (α3).
Za određivanje ovih parcijalnih koeficijenata oticaja, daju se vrednosti u Tabelama 7.1, 7.2 i 7.3, gde se za određeni sliv, definisan nagibom, propustljivošću i obraslošću terena nalaze odgovarajuće vrednosti. Koeficijent oticaja jednak je zbiru tri faktora:
catchment area (Pantelić, 1966).
The starting equation for the medial hydro-module of the drainage system:
Where: qs – is the medial hydro-module of drainage (l s-1 ha-1), α – run-off coefficient, h – relevant precipitation level (mm), t – relevant precipitation time length (days), τ – reach time, the path of a drop of water from the remotest part of the catchment to the reservoir (days).
If we multiply the equation above by the coefficient that indicates the ratio of maximum and medium run-off, which is 1.7 in the conditions that apply to Hungary (it can be used for Vojvodina too), we get the per unit hydro-module for maximum drainage - qmax (l s-1 ha-1):
The run-off coefficient plays an important role in determining the hydro-module for the run-off.
Several factors need to be known for determining this, such as: permeability, gradient, land cultivation method, type of soil surface. In the main plan for the Čurug-Žabalj drainage system (Pantelić, 1966), we can read that the functional changes in the run-off coefficient on a monthly basis are caused by the following:
(1) land gradient (α1);
(2) soil’s permeability (α2);
(3) land cover (α3).
For determining the partial coefficients of run-off, the values are provided in Table 7.1, 7.2 and 7.3, where the relevant values of the water flow specified in relation to the gradient, the permeability and the vegetation that covers the land can be found. The run-off coefficient equals the sum of the three coefficients given.
They used the pedologic map of Vojvodina for determining the α2 partial coefficient (Živković et al., 1972). Defining the α2 partial coefficient was done based on the proportions of various soil types and their permeability levels in the given area. In his study Miljković (2005) classifies soil into drainage categories, based on its chemical characteristics. He created the following five drainage classes and described them as follows:
(1) 1st drainage class – soil with naturally weak drainage characteristics, so its surface is very much threatened by excess water;
(2) 2nd drainage class – soil with naturally weak drainage characteristics, so its surface is under medium level threat from excess water;
(3) 3rd drainage class – soil with naturally insufficient drainage characteristics, so its surface is moderately threatened by excess water;
τ
Tabela 7.1. Parcijalni koeficijent oticaja u funkciji pada terena (α1) Nagib terena Koeficijent α1
>35 % 0,22 – 0,25 – 0,30 11 – 35 % 0,12 – 0,18 – 0,20 3,5 – 11 % 0,06 – 0,08 – 0,10
<3,5 % 0,01 – 0,03 – 0,05
Tabela 7.2. Parcijalni koeficijent oticaja u funkciji propustljivosti zemljišta (α2)
Propustljivost zemljišta Koeficijent α2 Vrlo nepropusno zemljište 0,22 – 0,26 – 0,30 Srednje propusno zemljište 0,12 – 0,16 – 0,20
Propusno zemljište 0,06 – 0,08 – 0,10
Vrlo propusno zemljište 0,03 – 0,04 – 0,05
Tabela 7.3. Parcijalni koeficijent oticaja u funkciji obraslosti zemljišta (α3)
Obraslost zemljišta Koeficijent α3
Za neobraslo zemljište 0,22 – 0,26 – 0,30
Za rit i pašnjake 0,17 – 0,21 – 0,25
Za kultivisano zemljište 0,07 – 0,11 – 0,15 Za šume i zemljišta labave strukture (peskovi) 0,03 – 0,04 – 0,05
U svrhu određivanja parcijlnog koeficijenta α2, korišćena je Pedološka karta zemlji-šta Vojvodine (Živković et al., 1972). Koeficijent α2 dobijen je na osnovu procentu-alne zastupljenosti različitih tipova zemljišta na ovom području i njihovih drenažnih karakteristika. U radu je, prema Miljkoviću (2005), izvršena podela zemljišta na dre-nažne klase, na osnovu prosečnih graničnih vrednosti njihovih vodnih konstanti i glavnih hemiskih parametara. Tako su zemljišta podeljena na pet drenažnih klasa, sledećih karakteristika:
(1) I drenažna klasa – zemljišta koja su prirodno vrlo slabo drenirana, te su njihove površine visokog stepena ugroženosti od suvišnih voda;
(2) II drenažna klasa – zemljišta koja su prirodno slabo drenirana, te su nji-hove površine srednjeg stepena ugroženosti od suvišnih voda;
(3) III drenažna klasa – zemljišta koja su prirodno nedovoljno drenirana, te su njihove površine umerenog stepena ugroženosti od suvišnih voda;
(4) IV drenažna klasa – teksturno lakša zemljišta, koja su prirodno umereno drenirana, te su njihove površine niskog stepena ugroženosti od suvišnih voda;
(5) V drenažna klasa – teksturno laka zemljišta, koja su prirodno dobro dre-nirana, te njihove površine nisu ugrožrne od suvišnih voda i ne zahtevaju odvodnjavanje.
Vrednost koeficijenta α3 dobijena je analizom karte zemljišnog pokrivača CORINE Land Cover 2012 (EEA, 2012). Ova karta sadrži bazu sa podacima o korišćenju zemljišta i pripadajućim površinama. Podaci o zemljišnom pokrivaču, mogu se dobiti na osnovu koda iz baze podataka i korišćenjem CORINE nomenklature (Nestorov i
Protić, 2006). Analiza ovih prostornih podataka i izrada karata područja, izvršena je korišćenjem GIS alata.
Bilo da se radi o pojedinačnoj lokaciji ili širem području, određivanje visine efek-tivnih padavina, koje se koriste prilikom predviđanja poplavnih talasa, posebno u determinističkim metodama, mora biti zasnovano na trajanju padavina visokog intenziteta (olujne padavine) ili vremenu koncentracije sliva (Gericke and Plessis, 2011). Vreme koncentracije sliva (τ) je ključni vremenski parametar odziva sliva, potreban za predviđanje maksimalnih zapremina oticaja (Perdikaris et al., 2018).
Vreme koncentracije sliva (τ) predstavlja vreme doticaja kišne kapi od najudaljenije tačke sliva do njegovog recipijenta, i ono je u Projektu (Pantelić, 1966) određeno jednačinom Venturija, gde je izraženo u funkciji površine sliva:
(4) 4th drainage class – soil with a lighter texture, which has a moderate natural drainage capacity, so its surface is under a low level of threat from excess water;
(5) 5th drainage class – soil with a light texture, which has good natural drainage characteristics, so its surface isn’t threatened by excess water – it doesn’t require drainage.
The value of the α3 coefficient was determined by analysing the land cover map with the help of CORINE Land Cover 2012 (EEA, 2012). This map contains data on how the land is used and on the size of the plots. Land cover data can be extracted by using the database codes and the CORINE nomenclature (Nestorov and Protić, 2006). Analysing data on the area and creating the map was done using GIS methods.
In the case of both individual plots and large areas, determining the effective precipitation level – which is used in forecasting floods – must be based on high intensity (storm) precipitation time periods or on the time period of the water flow’s concentration (Gericke and Plessis, 2011). The time period of the water flow’s concentration (τ) is a key time factor in the catchment system’s reaction, which is necessary for forecasting the maximum run-off volume (Perdikaris et al., 2018).
The time period of the water flow’s concentration (τ) indicates the time a drop of rain needs to get from the remotest part of the catchment to the reservoir – in the project (Pantelić, 1966) this was determined by Venturi’s equation, in relation to the surface of the catchment area:
Where F – is the territory of the catchment area in km2.
The relevant precipitation level was calculated by using Montanari’s climate function, and it is calculated separately for each area analysed:
Where: h – is the relevant precipitation level (mm), a and n – constants, which depend on the hydrologic characteristics of the area analysed, while t indicates the time length of precipitation (in days).
According to Rajić and Josimov-Dunđerski (2009), the following coefficients are valid for the territory of Vojvodina, a=64 (this indicates the average maximum daily rainfall in Vojvodina) and n=0,415 – this means that Montanari’s function looks like this:
Based on Montanari’s function and the concentration time of the catchment (τ), the formula for the relevant precipitation time period is:
F
Merodavna visina padavina, dobijena je korišćenjem klimatske funkcije Montana-rija, koja se izvodi za svako analizirano područje posebno, i glasi:
(4) 4th drainage class – soil with a lighter texture, which has a moderate natural drainage capacity, so its surface is under a low level of threat from excess water;
(5) 5th drainage class – soil with a light texture, which has good natural drainage characteristics, so its surface isn’t threatened by excess water – it doesn’t require drainage.
The value of the α3 coefficient was determined by analysing the land cover map with the help of CORINE Land Cover 2012 (EEA, 2012). This map contains data on how the land is used and on the size of the plots. Land cover data can be extracted by using the database codes and the CORINE nomenclature (Nestorov and Protić, 2006). Analysing data on the area and creating the map was done using GIS methods.
In the case of both individual plots and large areas, determining the effective precipitation level – which is used in forecasting floods – must be based on high intensity (storm) precipitation time periods or on the time period of the water flow’s concentration (Gericke and Plessis, 2011). The time period of the water flow’s concentration (τ) is a key time factor in the catchment system’s reaction, which is necessary for forecasting the maximum run-off volume (Perdikaris et al., 2018).
The time period of the water flow’s concentration (τ) indicates the time a drop of rain needs to get from the remotest part of the catchment to the reservoir – in the project (Pantelić, 1966) this was determined by Venturi’s equation, in relation to the surface of the catchment area:
Where F – is the territory of the catchment area in km2.
The relevant precipitation level was calculated by using Montanari’s climate function, and it is calculated separately for each area analysed:
Where: h – is the relevant precipitation level (mm), a and n – constants, which depend on the hydrologic characteristics of the area analysed, while t indicates the time length of precipitation (in days).
According to Rajić and Josimov-Dunđerski (2009), the following coefficients are valid for the territory of Vojvodina, a=64 (this indicates the average maximum daily rainfall in Vojvodina) and n=0,415 – this means that Montanari’s function looks like this:
Based on Montanari’s function and the concentration time of the catchment (τ), the formula for the relevant precipitation time period is:
F
Gde su: h – merodavna visina padavina (mm), a i n - konstante koje zavise od hidro-loških svojstava analiziranog područja, dok t predstavlja trajanje padavina (dani).
Rajić i Josimov-Dunđerski (2009) navode da za područje Vojvodine važe vrednosti koeficijenata a=64 (što predstavlja prosečnu jednodnevnu maksimalnu visinu pada-vina za područje Vojvodine) i n=0,415, tada Montanarijeva funkcija dobija oblik:
(4) 4th drainage class – soil with a lighter texture, which has a moderate natural drainage capacity, so its surface is under a low level of threat from excess water;
(5) 5th drainage class – soil with a light texture, which has good natural drainage characteristics, so its surface isn’t threatened by excess water – it doesn’t require drainage.
The value of the α3 coefficient was determined by analysing the land cover map with the help of CORINE Land Cover 2012 (EEA, 2012). This map contains data on how the land is used and on the size of the plots. Land cover data can be extracted by using the database codes and the CORINE nomenclature (Nestorov and Protić, 2006). Analysing data on the area and creating the map was done using GIS methods.
In the case of both individual plots and large areas, determining the effective precipitation level – which is used in forecasting floods – must be based on high intensity (storm) precipitation time periods or on the time period of the water flow’s concentration (Gericke and Plessis, 2011). The time period of the water flow’s concentration (τ) is a key time factor in the catchment system’s reaction, which is necessary for forecasting the maximum run-off volume (Perdikaris et al., 2018).
The time period of the water flow’s concentration (τ) indicates the time a drop of rain needs to get from the remotest part of the catchment to the reservoir – in the project (Pantelić, 1966) this was determined by Venturi’s equation, in relation to the surface of the catchment area:
Where F – is the territory of the catchment area in km2.
The relevant precipitation level was calculated by using Montanari’s climate function, and it is calculated separately for each area analysed:
Where: h – is the relevant precipitation level (mm), a and n – constants, which depend on the hydrologic characteristics of the area analysed, while t indicates the time length of precipitation (in days).
According to Rajić and Josimov-Dunđerski (2009), the following coefficients are valid for the territory of Vojvodina, a=64 (this indicates the average maximum daily rainfall in Vojvodina) and n=0,415 – this means that Montanari’s function looks like this:
Based on Montanari’s function and the concentration time of the catchment (τ), the formula for the relevant precipitation time period is:
F
Na osnovu funkcije Montanarija i vremena koncentracije sliva (τ), formula za vreme trajanja merodavne kiše:
(4) 4th drainage class – soil with a lighter texture, which has a moderate natural drainage capacity, so its surface is under a low level of threat from excess water;
(5) 5th drainage class – soil with a light texture, which has good natural drainage characteristics, so its surface isn’t threatened by excess water – it doesn’t require drainage.
The value of the α3 coefficient was determined by analysing the land cover map with the help of CORINE Land Cover 2012 (EEA, 2012). This map contains data on how the land is used and on the size of the plots. Land cover data can be extracted by using the database codes and the CORINE nomenclature (Nestorov and Protić, 2006). Analysing data on the area and creating the map was done using GIS methods.
In the case of both individual plots and large areas, determining the effective precipitation level – which is used in forecasting floods – must be based on high intensity (storm) precipitation time periods or on the time period of the water flow’s concentration (Gericke and Plessis, 2011). The time period of the water flow’s concentration (τ) is a key time factor in the catchment system’s reaction, which is necessary for forecasting the maximum run-off volume (Perdikaris et al., 2018).
The time period of the water flow’s concentration (τ) indicates the time a drop of rain needs to get from the remotest part of the catchment to the reservoir – in the project (Pantelić, 1966) this was determined by Venturi’s equation, in relation to the surface of the catchment area:
Where F – is the territory of the catchment area in km2.
The relevant precipitation level was calculated by using Montanari’s climate function, and it is calculated separately for each area analysed:
Where: h – is the relevant precipitation level (mm), a and n – constants, which depend on the hydrologic characteristics of the area analysed, while t indicates the time length of precipitation (in days).
According to Rajić and Josimov-Dunđerski (2009), the following coefficients are valid for the territory of Vojvodina, a=64 (this indicates the average maximum daily rainfall in Vojvodina) and
According to Rajić and Josimov-Dunđerski (2009), the following coefficients are valid for the territory of Vojvodina, a=64 (this indicates the average maximum daily rainfall in Vojvodina) and